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Front Cover -- Networks of Invasion: A Synthesis of Concepts -- Copyright -- Contents -- Contributors -- Preface -- Acknowledgements -- References -- Chapter One: Impacts of Invasive Species on Food Webs: A Review of Empirical Data -- 1. Introduction -- 2. Definitions and Limits -- 2.1. Invasive Species: An ``Anthropocentric Concept´´ -- 2.2. Measuring Impacts on Food Webs: Objects of Study and Methodology -- 3. Local Effects: Effect of Invaders at One or Two Steps of Distance -- 3.1. Top-Down Effects -- 3.1.1. Invasive Predators May Have Large Impacts on Resident Species -- 3.1.2. Ecological and Evolutionary Naïveté Exacerbate the Impact of Invasive Predators -- 3.1.3. Top-Down Effect of Invasions May Result in Trophic Cascades -- 3.2. Lateral Effects of Invaders: Exploitative Competition -- 3.2.1. Exploitative Competition is Expressed as a Two-Step Path in a Food Web -- 3.2.2. Extinctions by Competition Between Introduced and Native Species Are Relatively Rare -- 3.2.3. Asymmetry in Competition Impacts, Lack of Coevolutionary History, and Invasion Filter -- 3.2.4. Exploitative Competition May Be Mixed With Other Interactions -- 3.2.5. The Case of Invasive Fruit Flies Illustrates Asymmetric Competitive Interactions Between Invaders and Residents -- 3.3. Bottom-Up Effects of Invaders -- 3.3.1. Invaders Provide Direct Benefits but Indirect Costs to Local Predators -- 3.3.2. Coevolutionary History and Invasion Filter Underlie Enemy Release -- 3.4. Apparent Competition Between Invaders and Residents -- 3.5. Facilitation, Mutualisms, and Engineering: Nontrophic Indirect Interactions -- 4. Global Effects: Invasions at Food Web Scale -- 4.1. Food Web Structure as a Biotic Filter -- 4.1.1. Species Diversity Might Increase Food Web Resistance to Invasion -- 4.1.2. Effects of Food Web Structure on Invasion: Beyond Diversity.

Front Cover -- Next Generation Biomonitoring: Part 2 -- Copyright -- Contents -- Contributors -- Preface -- References -- Acknowledgements -- Chapter One: Bioinformatics for Biomonitoring: Species Detection and Diversity Estimates Across Next-Generation Sequencin ... -- 1. Introduction -- 2. Materials and Methods -- 2.1. Mock Communities -- 2.2. Library Preparation for Roche 454 -- 2.3. Library Preparation for Illumina MiSeq -- 2.4. Bioinformatics and Data Analysis -- 2.5. Assigning Taxonomy to OTUs and Dereplicated Sequences -- 3. Results -- 3.1. Sequence and Read Depth -- 3.2. OTU Clustering and the Effect of Singletons -- 3.3. Species Detection -- 3.4. OTU Precision -- 3.5. Impact of Merging and Appending MiSeq Reads on Species Detection and OTU Estimates -- 4. Discussion -- 4.1. Read Depth and Singletons -- 4.2. OTU Clustering -- 4.3. Experimental Design -- 4.4. Implications for Biomonitoring -- 5. Conclusions -- Acknowledgements -- References -- Chapter Two: Linking DNA Metabarcoding and Text Mining to Create Network-Based Biomonitoring Tools: A Case Study on Borea ... -- 1. Introduction -- 1.1. Ecological Networks as Biomonitoring Tools -- 1.2. New Tools to Rapidly Assess Biodiversity and Annotate It With Ecological Information -- 1.3. Freshwater Biodiversity Hotspots as Candidates for Exploring Novel Approaches for Biodiversity Assessment -- 1.4. Exploring the Generation of DNA Ecological Networks for Aquatic Biomonitoring -- 2. Building Heuristic Food Webs for Wetland Biomonitoring: A Case Study -- 2.1. DNA Sample Collection, Metabarcoding, and Bioinformatics Pipeline -- 2.2. Development of Text-Mining Pipeline for Traits of Freshwater Organisms -- 2.3. Evaluation, and Iterative Refinements to Text-Mining Pipeline for Body Size -- 2.4. Rule-Based Procedure for Retrieving Trait Information for Heuristic Food Web Construction

Front Cover -- Next Generation Biomonitoring: Part 1 -- Copyright -- Contents -- Contributors -- Preface -- Acknowledgements -- Chapter One: Biomonitoring for the 21st Century: Integrating Next-Generation Sequencing Into Ecological Network Analysis -- 1. Introduction -- 2. How Are Ecological Networks Useful for Biomonitoring? -- 2.1. Traditional Biomonitoring Is Typically Descriptive and Rarely Provides an Understanding of the Underlying Mechanisms ... -- 2.2. Ecological Networks Provide a Framework to Describe and Monitor Ecological Processes and Ecosystem Functions -- 2.3. Ecological Network Structure Characterizes Ecosystem Properties -- 2.4. Knowledge of Ecological Networks Helps to Assess the Effect(s) of Environmental Changes on Ecosystem Processes and A ... -- 2.5. The Robustness of Networks of Ecological Networks: Applications for Understanding Species and Habitat Loss, Restorat ... -- 3. Ecological Networks Can Be Challenging to Build Using Conventional Approaches -- 4. Combining NGS With ENA: Opportunities and Challenges -- 4.1. Using NGS to Construct Ecological Networks -- 4.2. PCR Bias and Abundance Estimation in NGS Community Analyses -- 4.3. NGS Without a Prior PCR Step -- 4.4. Detection of Species Interactions Using Molecular Tools -- 4.5. How to Deal With Interactions Not Directly Resolved by NGS: Are Species Association Networks Species Interaction Net ... -- 5. Machine Learning as a Way to Rapidly Build Molecular Ecological Networks in a Rapid and Reliable Way? -- 5.1. Learning Ecological Networks From Data -- 5.2. Exploiting eDNA-Derived Information as a Source for Network Data -- 6. NGS Network Data Sharing -- 6.1. The Importance of a Dedicated NGS Network Database: Linking DNA Sequences and Ecological Interactions to Limit Speci

Front Cover -- Large-Scale Ecology: Model Systems to Global Perspectives -- Copyright -- Contents -- Contributors -- Preface -- References -- Part I: Large Spatial Scale Ecology -- Chapter One: The Unique Contribution of Rothamsted to Ecological Research at Large Temporal Scales -- 1. Introduction to Long-Term Ecological Research at Rothamsted -- 1.1. The Rothamsted Classical Experiments -- 1.1.1. The Park Grass Experiment -- 1.1.2. The Broadbalk Wheat Experiment -- 1.2. Highfield, Fosters and Woburn Ley-Arable Experiments -- 1.3. Broadbalk and Geescroft Wildernesses -- 1.4. The Rothamsted Insect Survey -- 2. Monitoring the Impact of Environmental Change -- 2.1. Response of Plant Communities to Environmental Change -- 2.2. Response of Plant Pathogens to Environmental Change -- 2.3. Phenological Change and Trophic Asynchrony -- 3. Community Ecology -- 3.1. Value of the Rothamsted Experiments to Plant Community Ecology -- 3.1.1. Reconciling Resource Ratio and C-S-R Theories of Plant Community Assembly -- 3.2. Trophic Interactions -- 3.3. Environmental Drivers of Insect Abundance and Distribution -- 4. Ecosystem Stability and Resilience -- 4.1. Plant Community Stability -- 4.2. Resilience of Ecosystem Function -- 5. Evolutionary Ecology -- 5.1. Beyond Snaydon and Davies -- 5.2. Evolutionary Ecology of Pathogens and Weeds -- 6. Soil Microbial Ecology -- 6.1. Microbial Communities on the PGE -- 6.2. Microbial Communities on Broadbalk -- 7. Conclusion -- Acknowledgements -- References -- Chapter Two: How Agricultural Intensification Affects Biodiversity and Ecosystem Services -- 1. Introduction -- 1.1. General Objective and Goals -- 2. The CAP and AI -- 2.1. CAP as a Driver of Agriculture in Europe -- 2.2. How Does CAP Affect AI? -- 2.3. How Does CAP Affect Biodiversity and Ecosystem Services Through AI?.